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More Data Science Magic: Visualizing and Sharing Results

More Data Science MagicIn our previous post, we described what business users could accomplish during data discovery, selection and analysis. We used the TIBCO Spotfire, Tableau Desktop and Hortonworks Platform tools to show how business users can build serious data scientist chops without a PhD. This time, we complete the workflow by reviewing the platform’ data visualization and sharing capabilities.

Visualize Data
A visual summary of information makes it easy to recognize patterns and outliers in large data sets. Visualization software has been around for a while. But modern analytics platforms take visualization to new levels of data processing power, versatility and user convenience.(more…)

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Self-Service Data Magic: No Wands, Just Great Tools

Big Data AnalyticsNot long ago, we ran a post describing how business users can learn to become data scientists. No, we didn’t resort to spells or incantations. Instead, we described tools, capabilities and best practices that help analysis-minded business users get insight directly from their data.In this seven-part series, we’re devoting a post to each of the six enablers mentioned in our earlier post.First up: the most advanced self-service capabilities business users can perform on leading Big Data analytics platforms.

DIY Big Data Analytics without Tears

Here’s a summary of advanced capabilities and why TIBCO Spotfire, Tableau Desktop and Hortonworks can help you perform. It’s a compilation: no single product has all the bells and whistles described here. But it can give you an idea of what you might accomplish at each stage of the analysis process.(more…)

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Stepping Up to Big Data Analytics: Hadoop and TERR

Big Data analytics is the analysis of data sets that often contain many types of data. It’s designed to help companies extract value from huge volumes of data. The goal: find hidden patterns, market trends and other useful business information to enable more accurate and timely business decisions.Mainstream data handling methods used for relational databases cannot process unstructured such as images, email, sound files and EDI messages, which are common elements of Big Data. And these traditional methods can’t handle the processing demands posed by very large data sets and the need for frequent or continuous updates.So, many organizations are giving Hadoop and related tools a serious look. TIBCO™ has added TERR, its enterprise-grade analytics engine, to Hadoop. The combination provides an open source software framework that supports processing of large and diverse data sets across clustered systems.

What Puts the Oomph into Big Data Analytics Solutions?
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